{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}R:\WSV2\TBu_BMa\Subsidies Project\Results\Close Substitutes.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}22 Feb 2021, 09:58:58
{txt}
{com}. 
. 
. ************************************************************************************************************************************************
. 
. ***AUSTRIA, 2009 
. 
. ****Refrigerators
. 
. clear all
{res}{txt}
{com}. 
. use "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta"
{txt}
{com}. keep                    if country=="Austria"
{txt}(2,023,539 observations deleted)

{com}. keep                    if year==2009
{txt}(448,194 observations deleted)

{com}. keep                    if category=="refrigerator"
{txt}(17,532 observations deleted)

{com}. 
. by id, sort:    egen mean_price=mean(price) if year==2009 & month<=5
{txt}(16081 missing values generated)

{com}. sum mean_price

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 2}mean_price {c |}{res}      8,015    675.8209    515.0079         79       8990
{txt}
{com}. 
. encode nofrostsys,              gen(nofrost)
{txt}
{com}. encode construction,    gen(constr)
{txt}
{com}. encode main_type,               gen(type)
{txt}
{com}. 
. 
. collapse (mean) nofrost type constr mean_price, by(id year treataf)
{txt}
{com}. 
. cem nofrost type constr mean_price(200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600) , treatment(treataf) k2k
{res}
{txt}Matching Summary:
-----------------
Number of strata: {res}166
{txt}Number of matched strata: {res}58

           {txt}   0     1
      All  {res}1725   283
{txt}  Matched  {res} 261   261
{txt}Unmatched  {res}1464    22


{txt}Multivariate L1 distance: {res}.07662835

{txt}Univariate imbalance:

                 L1     mean      min      25%      50%      75%      max
   nofrost  {res}      0        0        0        0        0        0        0
{txt}      type  {res}      0        0        0        0        0        0        0
{txt}    constr  {res}      0        0        0        0        0        0        0
{txt}mean_price  {res} .04981   6.4221   62.091   8.6028  -4.9355        .        .
{txt}
{com}. 
. 
. keep id cem_matched
{txt}
{com}. 
. merge m:m id using "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta"
{res}
{txt}{col 5}Result{col 38}# of obs.
{col 5}{hline 41}
{col 5}not matched{col 30}{res}       2,184,317
{txt}{col 9}from master{col 30}{res}               0{txt}  (_merge==1)
{col 9}from using{col 30}{res}       2,184,317{txt}  (_merge==2)

{col 5}matched{col 30}{res}         329,044{txt}  (_merge==3)
{col 5}{hline 41}

{com}. drop _merge
{txt}
{com}. 
. by id, sort: egen sumcema9=sum(cem_matched)
{txt}
{com}. drop cem_matched
{txt}
{com}. 
. 
. save "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta", replace
{txt}file R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta saved

{com}. 
. 
. ****Freezers
. 
. clear all
{res}{txt}
{com}. use "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta"
{txt}
{com}. 
. keep                    if country=="Austria"
{txt}(2,023,539 observations deleted)

{com}. keep                    if year==2009
{txt}(448,194 observations deleted)

{com}. keep                    if category=="freezer"
{txt}(35,148 observations deleted)

{com}. 
. by id, sort:    egen mean_price=mean(price) if year==2009 & month<=5
{txt}(4190 missing values generated)

{com}. sum mean_price

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 2}mean_price {c |}{res}      2,290    520.8469    324.7139     100.84    4823.08
{txt}
{com}. 
. encode nofrostsys,              gen(nofrost)
{txt}
{com}. encode construction,    gen(constr)
{txt}
{com}. encode type_freezer,    gen(typef)
{txt}
{com}. 
. collapse (mean) nofrost typef constr mean_price, by(id year treataf)
{txt}
{com}. 
. cem nofrost typef constr mean_price(200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600), treatment(treataf) k2k
{res}
{txt}Matching Summary:
-----------------
Number of strata: {res}57
{txt}Number of matched strata: {res}20

           {txt}  0    1
      All  {res}442   98
{txt}  Matched  {res} 63   63
{txt}Unmatched  {res}379   35


{txt}Multivariate L1 distance: {res}.11111111

{txt}Univariate imbalance:

                L1    mean     min     25%     50%     75%     max
   nofrost  {res}     0       0       0       0       0       0       0
{txt}     typef  {res}     0       0       0       0       0       0       0
{txt}    constr  {res}     0       0       0       0       0       0       0
{txt}mean_price  {res}.09524  6.0967  11.031  24.799  9.5986       .       .
{txt}
{com}. 
. keep id cem_matched
{txt}
{com}. 
. merge m:m id using "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta"
{res}
{txt}{col 5}Result{col 38}# of obs.
{col 5}{hline 41}
{col 5}not matched{col 30}{res}       2,431,107
{txt}{col 9}from master{col 30}{res}               0{txt}  (_merge==1)
{col 9}from using{col 30}{res}       2,431,107{txt}  (_merge==2)

{col 5}matched{col 30}{res}          82,254{txt}  (_merge==3)
{col 5}{hline 41}

{com}. 
. drop _merge 
{txt}
{com}. by id, sort: egen sumcemfa9=sum(cem_matched)
{txt}
{com}. drop cem_matched
{txt}
{com}. 
. gen     controlma9=0
{txt}
{com}. replace controlma9=1 if (sumcema9>0 & treataf==0)|(sumcemfa9>0 & treataf==0)
{txt}(52,737 real changes made)

{com}. 
. codebook id if controlma9==1

{txt}{hline}
{res}id{right:(unlabeled)}
{txt}{hline}

{col 19}type:  string ({res}str11{txt})

{col 10}unique values:  {res}324{col 51}{txt}missing "":  {res}0{txt}/{res}52,737

{txt}{col 15}examples:  {res}"27024857"
{col 26}"29659065"
{col 26}"35844253"
{col 26}"47150974"
{txt}
{com}. 
. save "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta", replace
{txt}file R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta saved

{com}. 
. 
. 
. 
. ************************************************************************************************************************************************
. ***AUSTRIA, 2010 
. 
. ****Refrigerators
. clear all
{res}{txt}
{com}. 
. use "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta"
{txt}
{com}. 
. 
. keep                    if country=="Austria"
{txt}(2,023,539 observations deleted)

{com}. keep                    if year==2010
{txt}(450,090 observations deleted)

{com}. keep                    if category=="refrigerator"
{txt}(16,404 observations deleted)

{com}. 
. by id, sort:    egen mean_price=mean(price) if year==2010 & month<=5
{txt}(15728 missing values generated)

{com}. 
. encode nofrostsys,              gen(nofrost)
{txt}
{com}. encode construction,    gen(constr)
{txt}
{com}. encode main_type,               gen(type)
{txt}
{com}. 
. collapse (mean) nofrost type constr mean_price, by(id year treataf)
{txt}
{com}. 
. 
. cem nofrost type constr mean_price(200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600), treatment(treataf) k2k
{res}
{txt}Matching Summary:
-----------------
Number of strata: {res}164
{txt}Number of matched strata: {res}86

           {txt}   0     1
      All  {res}1551   393
{txt}  Matched  {res} 334   334
{txt}Unmatched  {res}1217    59


{txt}Multivariate L1 distance: {res}.08682635

{txt}Univariate imbalance:

                 L1     mean      min      25%      50%      75%      max
   nofrost  {res}      0        0        0        0        0        0        0
{txt}      type  {res}      0        0        0        0        0        0        0
{txt}    constr  {res}      0        0        0        0        0        0        0
{txt}mean_price  {res} .03593  -15.077   22.882  -1.1318   20.104        .        .
{txt}
{com}. 
. keep id cem_matched
{txt}
{com}. 
. merge m:m id using "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta"
{res}
{txt}{col 5}Result{col 38}# of obs.
{col 5}{hline 41}
{col 5}not matched{col 30}{res}       2,170,523
{txt}{col 9}from master{col 30}{res}               0{txt}  (_merge==1)
{col 9}from using{col 30}{res}       2,170,523{txt}  (_merge==2)

{col 5}matched{col 30}{res}         342,838{txt}  (_merge==3)
{col 5}{hline 41}

{com}. 
. drop _merge
{txt}
{com}. 
. by id, sort: egen sumcema10=sum(cem_matched)
{txt}
{com}. 
. drop cem_matched
{txt}
{com}. 
. save "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta", replace
{txt}file R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta saved

{com}. 
. 
. ****Freezers
. clear all
{res}{txt}
{com}. 
. use "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta"
{txt}
{com}. 
. 
. keep                    if country=="Austria"
{txt}(2,023,539 observations deleted)

{com}. keep                    if year==2010
{txt}(450,090 observations deleted)

{com}. keep                    if category=="freezer"
{txt}(33,660 observations deleted)

{com}. 
. by id, sort:    egen mean_price=mean(price) if year==2010 & month<=5
{txt}(4132 missing values generated)

{com}. 
. 
. encode nofrostsys,              gen(nofrost)
{txt}
{com}. encode construction,    gen(constr)
{txt}
{com}. encode type_freezer,    gen(typef)
{txt}
{com}. 
. collapse (mean) nofrost typef constr mean_price, by(id year treataf)
{txt}
{com}. 
. cem nofrost typef constr mean_price(200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600), treatment(treataf) k2k
{res}
{txt}Matching Summary:
-----------------
Number of strata: {res}57
{txt}Number of matched strata: {res}19

           {txt}  0    1
      All  {res}374  132
{txt}  Matched  {res} 76   76
{txt}Unmatched  {res}298   56


{txt}Multivariate L1 distance: {res}.10526316

{txt}Univariate imbalance:

                 L1     mean      min      25%      50%      75%      max
   nofrost  {res}      0        0        0        0        0        0        0
{txt}     typef  {res}      0        0        0        0        0        0        0
{txt}    constr  {res}      0        0        0        0        0        0        0
{txt}mean_price  {res} .06579   6.4732    4.128   8.2618  -17.974        .        .
{txt}
{com}. 
. 
. keep id cem_matched
{txt}
{com}. 
. merge m:m id using "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta"
{res}
{txt}{col 5}Result{col 38}# of obs.
{col 5}{hline 41}
{col 5}not matched{col 30}{res}       2,426,102
{txt}{col 9}from master{col 30}{res}               0{txt}  (_merge==1)
{col 9}from using{col 30}{res}       2,426,102{txt}  (_merge==2)

{col 5}matched{col 30}{res}          87,259{txt}  (_merge==3)
{col 5}{hline 41}

{com}. drop _merge
{txt}
{com}. 
. by id, sort: egen sumcemfa10=sum(cem_matched)
{txt}
{com}. drop cem_matched
{txt}
{com}. 
. 
. gen     controlma10=0
{txt}
{com}. replace controlma10=1 if (sumcema10>0 & treataf==0)|(sumcemfa10>0 & treataf==0)
{txt}(78,856 real changes made)

{com}. 
. codebook id if controlma10==1

{txt}{hline}
{res}id{right:(unlabeled)}
{txt}{hline}

{col 19}type:  string ({res}str11{txt}), but longest is str10

{col 10}unique values:  {res}410{col 51}{txt}missing "":  {res}0{txt}/{res}78,856

{txt}{col 15}examples:  {res}"28565507"
{col 26}"33098309"
{col 26}"37941040"
{col 26}"50312414"
{txt}
{com}. 
. 
. save "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta", replace
{txt}file R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta saved

{com}. 
. 
. 
. ************************************************************************************************************************************************
. ***HUNGARY, 2016
. 
. clear all
{res}{txt}
{com}. 
. ****Refrigerators
. 
. use "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta" 
{txt}
{com}. 
. keep                    if country=="Hungary"
{txt}(2,200,397 observations deleted)

{com}. keep                    if year==2016
{txt}(285,832 observations deleted)

{com}. keep                    if category=="refrigerator"
{txt}(12,312 observations deleted)

{com}. 
. by id, sort:    egen mean_price=mean(price_eur) if year==2016 & month<=5
{txt}(10335 missing values generated)

{com}. sum mean_price

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 2}mean_price {c |}{res}      4,485    498.4145    370.6435   82.28635   3635.311
{txt}
{com}. 
. encode nofrostsys,              gen(nofrost)
{txt}
{com}. encode construction,    gen(constr)
{txt}
{com}. encode main_type,               gen(type)
{txt}
{com}. 
. collapse (mean) nofrost type constr mean_price, by(year id treathf) 
{txt}
{com}. 
. cem nofrost type constr mean_price(200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600), treatment(treathf) k2k
{res}
{txt}Matching Summary:
-----------------
Number of strata: {res}130
{txt}Number of matched strata: {res}77

           {txt}  0    1
      All  {res}572  663
{txt}  Matched  {res}451  451
{txt}Unmatched  {res}121  212


{txt}Multivariate L1 distance: {res}.09534368

{txt}Univariate imbalance:

                 L1     mean      min      25%      50%      75%      max
   nofrost  {res}      0        0        0        0        0        0        0
{txt}      type  {res}      0        0        0        0        0        0        0
{txt}    constr  {res}      0        0        0        0        0        0        0
{txt}mean_price  {res} .04213  -.65564   38.961   1.8919   -2.554        .        .
{txt}
{com}. 
. keep id cem_matched
{txt}
{com}. 
. merge m:m id using "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta" 
{res}
{txt}{col 5}Result{col 38}# of obs.
{col 5}{hline 41}
{col 5}not matched{col 30}{res}       2,329,483
{txt}{col 9}from master{col 30}{res}               0{txt}  (_merge==1)
{col 9}from using{col 30}{res}       2,329,483{txt}  (_merge==2)

{col 5}matched{col 30}{res}         183,878{txt}  (_merge==3)
{col 5}{hline 41}

{com}. drop _merge
{txt}
{com}. 
. by id, sort: egen sumcemh16=sum(cem_matched)
{txt}
{com}. drop cem_matched
{txt}
{com}. 
. 
. save "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta", replace
{txt}file R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta saved

{com}. 
. 
. ****Freezers
. 
. clear all
{res}{txt}
{com}. 
. use "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta" 
{txt}
{com}. 
. 
. keep                    if country=="Hungary"
{txt}(2,200,397 observations deleted)

{com}. keep                    if year==2016
{txt}(285,832 observations deleted)

{com}. keep                    if category=="freezer"
{txt}(24,132 observations deleted)

{com}. 
. by id, sort:    egen mean_price=mean(price_eur) if year==2016 & month<=5
{txt}(2040 missing values generated)

{com}. sum mean_price

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 2}mean_price {c |}{res}        960    365.9972    196.5548   101.0713    1241.51
{txt}
{com}. 
. encode nofrostsys,              gen(nofrost)
{txt}
{com}. encode construction,    gen(constr)
{txt}
{com}. encode type_freezer,    gen(typef)
{txt}
{com}. 
. collapse (mean) nofrost typef constr mean_price, by(year id treathf) 
{txt}
{com}. 
. cem nofrost typef constr mean_price(200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600), treatment(treathf) k2k
{res}
{txt}Matching Summary:
-----------------
Number of strata: {res}35
{txt}Number of matched strata: {res}18

           {txt}  0    1
      All  {res}102  148
{txt}  Matched  {res} 76   76
{txt}Unmatched  {res} 26   72


{txt}Multivariate L1 distance: {res}.03947368

{txt}Univariate imbalance:

                L1    mean     min     25%     50%     75%     max
   nofrost  {res}     0       0       0       0       0       0       0
{txt}     typef  {res}     0       0       0       0       0       0       0
{txt}    constr  {res}     0       0       0       0       0       0       0
{txt}mean_price  {res}.03947  3.8747  47.378   20.62  22.159       .       .
{txt}
{com}. 
. 
. keep id cem_matched
{txt}
{com}. 
. merge m:m id using "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta"
{res}
{txt}{col 5}Result{col 38}# of obs.
{col 5}{hline 41}
{col 5}not matched{col 30}{res}       2,469,980
{txt}{col 9}from master{col 30}{res}               0{txt}  (_merge==1)
{col 9}from using{col 30}{res}       2,469,980{txt}  (_merge==2)

{col 5}matched{col 30}{res}          43,381{txt}  (_merge==3)
{col 5}{hline 41}

{com}. drop _merge
{txt}
{com}. by id, sort: egen sumcemfh16=sum(cem_matched)
{txt}
{com}. 
. drop cem_matched
{txt}
{com}. 
. 
. gen             controlmh16=0
{txt}
{com}. replace         controlmh16=1           if (sumcemh16>0 & treathf==0)|(sumcemfh16>0 & treathf==0)
{txt}(139,712 real changes made)

{com}. codebook        id                                      if controlmh16==1

{txt}{hline}
{res}id{right:(unlabeled)}
{txt}{hline}

{col 19}type:  string ({res}str11{txt})

{col 10}unique values:  {res}1,054{col 51}{txt}missing "":  {res}0{txt}/{res}139,712

{txt}{col 15}examples:  {res}"54729872"
{col 26}"71175240"
{col 26}"77393402"
{col 26}"85700991"
{txt}
{com}. 
. 
. save "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta", replace
{txt}file R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta saved

{com}. 
. 
. 
. 
. 
. ************************************************************************************************************************************************
. ***AUSTRIA, 2010, WM
. clear all
{res}{txt}
{com}. use "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta" 
{txt}
{com}.  
. 
. keep                    if country=="Austria"
{txt}(2,023,539 observations deleted)

{com}. keep                    if (year==2009|year==2010)
{txt}(408,462 observations deleted)

{com}. keep                    if category=="washing machine"
{txt}(59,976 observations deleted)

{com}. 
. by id, sort:    egen mean_price=mean(price) if (year==2009 & month>=9|year==2010 & month<=1)
{txt}(17986 missing values generated)

{com}. sum mean_price  

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 2}mean_price {c |}{res}      3,398     580.461    281.0572      183.4   2132.675
{txt}
{com}. keep                    if year==2010
{txt}(11,052 observations deleted)

{com}. 
. encode type_wm,                 gen(type)
{txt}
{com}. destring loading_kg, replace
{txt}loading_kg: all characters numeric; {res}replaced {txt}as {res}double
{txt}
{com}. 
. collapse (mean) type loading_kg mean_price, by(year id treata)
{txt}
{com}. 
. cem type loading_kg mean_price(200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600), treatment(treata) k2k
{res}
{txt}Matching Summary:
-----------------
Number of strata: {res}113
{txt}Number of matched strata: {res}21

           {txt}  0    1
      All  {res}742  119
{txt}  Matched  {res} 86   86
{txt}Unmatched  {res}656   33


{txt}Multivariate L1 distance: {res}.09302326

{txt}Univariate imbalance:

                 L1     mean      min      25%      50%      75%      max
      type  {res}      0        0        0        0        0        0        0
{txt}loading_kg  {res} .04651  -.01163        0        0        0      -.5        0
{txt}mean_price  {res} .05814   4.8386   35.187   26.563    42.49        .        .
{txt}
{com}. 
. keep id cem_matched
{txt}
{com}. 
. merge m:m id using "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta"
{res}
{txt}{col 5}Result{col 38}# of obs.
{col 5}{hline 41}
{col 5}not matched{col 30}{res}       2,394,333
{txt}{col 9}from master{col 30}{res}               0{txt}  (_merge==1)
{col 9}from using{col 30}{res}       2,394,333{txt}  (_merge==2)

{col 5}matched{col 30}{res}         119,028{txt}  (_merge==3)
{col 5}{hline 41}

{com}. drop _merge
{txt}
{com}. 
. by id, sort: egen sumcemaw=sum(cem_matched)
{txt}
{com}. 
. drop cem_matched
{txt}
{com}. 
. 
. gen             controlmaw=0
{txt}
{com}. replace         controlmaw=1            if (sumcemaw>0 & treata==0)
{txt}(16,740 real changes made)

{com}. codebook        id                                      if controlmaw==1

{txt}{hline}
{res}id{right:(unlabeled)}
{txt}{hline}

{col 19}type:  string ({res}str11{txt}), but longest is str8

{col 10}unique values:  {res}172{col 51}{txt}missing "":  {res}0{txt}/{res}16,740

{txt}{col 15}examples:  {res}"34700645"
{col 26}"45232721"
{col 26}"53162880"
{col 26}"55730001"
{txt}
{com}. 
. 
. 
. save "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta", replace
{txt}file R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta saved

{com}. 
. 
. 
. 
. ************************************************************************************************************************************************
. ***HUNGARY, 2015, WM
. 
. clear all
{res}{txt}
{com}. 
. use "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta", 
{txt}
{com}. 
. keep                    if country=="Hungary"
{txt}(2,200,397 observations deleted)

{com}. keep                    if year==2015
{txt}(285,616 observations deleted)

{com}. keep                    if category=="washing machine"
{txt}(17,304 observations deleted)

{com}. 
. by id, sort:    egen mean_price=mean(price_eur) if year==2015 & month<=5
{txt}(6949 missing values generated)

{com}. 
. 
. encode type_wm,                 gen(type)
{txt}
{com}. destring loading_kg,    replace
{txt}loading_kg: all characters numeric; {res}replaced {txt}as {res}double
{txt}
{com}. 
. 
. collapse (mean) type loading_kg mean_price, by(year id treath)
{txt}
{com}. cem type loading_kg mean_price(200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600), treatment(treath) k2k
{res}
{txt}Matching Summary:
-----------------
Number of strata: {res}114
{txt}Number of matched strata: {res}41

           {txt}  0    1
      All  {res}499  338
{txt}  Matched  {res}272  272
{txt}Unmatched  {res}227   66


{txt}Multivariate L1 distance: {res}.16911765

{txt}Univariate imbalance:

                 L1     mean      min      25%      50%      75%      max
      type  {res}      0        0        0        0        0        0        0
{txt}loading_kg  {res} .03676   .01471        0        0        0        0        0
{txt}mean_price  {res} .09926   5.8548    9.417    7.308   3.5783  -7.2186        .
{txt}
{com}. 
. keep id cem_matched
{txt}
{com}. 
. merge m:m id using "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta"
{res}
{txt}{col 5}Result{col 38}# of obs.
{col 5}{hline 41}
{col 5}not matched{col 30}{res}       2,397,375
{txt}{col 9}from master{col 30}{res}               0{txt}  (_merge==1)
{col 9}from using{col 30}{res}       2,397,375{txt}  (_merge==2)

{col 5}matched{col 30}{res}         115,986{txt}  (_merge==3)
{col 5}{hline 41}

{com}. drop _merge
{txt}
{com}. 
. by id, sort: egen sumcemh15=sum(cem_matched)
{txt}
{com}. 
. drop cem_matched
{txt}
{com}. 
. 
. gen             controlmh15=0
{txt}
{com}. replace         controlmh15=1           if (sumcemh15>0 & treath==0)
{txt}(62,646 real changes made)

{com}. codebook        id                                      if controlmh15==1

{txt}{hline}
{res}id{right:(unlabeled)}
{txt}{hline}

{col 19}type:  string ({res}str11{txt})

{col 10}unique values:  {res}544{col 51}{txt}missing "":  {res}0{txt}/{res}62,646

{txt}{col 15}examples:  {res}"65587575"
{col 26}"75057898"
{col 26}"79276533"
{col 26}"85893718"
{txt}
{com}. 
. 
. save "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta", replace
{txt}file R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta saved

{com}. 
. 
. 
. ************************************************************************************************************************************************
. ***CROATIA, 2015, WM 
. clear all
{res}{txt}
{com}. 
. use "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta" 
{txt}
{com}. 
. keep                    if country=="Croatia"
{txt}(2,331,153 observations deleted)

{com}. keep                    if (year==2014|year==2015)
{txt}(147,300 observations deleted)

{com}. keep                    if category=="washing machine"
{txt}(21,252 observations deleted)

{com}. 
. by id, sort:    egen mean_price=mean(price_eur) if (year==2014& month>=11|year==2015 & month<=3)
{txt}(11648 missing values generated)

{com}. sum mean_price  

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 2}mean_price {c |}{res}      2,008    451.4766    224.2677   118.8801   1846.916
{txt}
{com}. keep                    if year==2015
{txt}(7,044 observations deleted)

{com}. 
. encode type_wm,                 gen(type)
{txt}
{com}. destring loading_kg, replace
{txt}loading_kg: all characters numeric; {res}replaced {txt}as {res}double
{txt}
{com}. 
. collapse type loading_kg mean_price, by(year id treatc)
{txt}
{com}. cem type loading_kg mean_price(200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600), treatment(treatc) k2k
{res}
{txt}Matching Summary:
-----------------
Number of strata: {res}93
{txt}Number of matched strata: {res}23

           {txt}  0    1
      All  {res}283  268
{txt}  Matched  {res}105  105
{txt}Unmatched  {res}178  163


{txt}Multivariate L1 distance: {res}.37142857

{txt}Univariate imbalance:

                L1    mean     min     25%     50%     75%     max
      type  {res}     0       0       0       0       0       0       0
{txt}loading_kg  {res}.04762  .02381       0       0       0       0       0
{txt}mean_price  {res}.24762  14.218  41.146  33.661  14.915       .       .
{txt}
{com}. 
. keep id cem_matched
{txt}
{com}. 
. merge m:m id using "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta"
{res}
{txt}{col 5}Result{col 38}# of obs.
{col 5}{hline 41}
{col 5}not matched{col 30}{res}       2,426,700
{txt}{col 9}from master{col 30}{res}               0{txt}  (_merge==1)
{col 9}from using{col 30}{res}       2,426,700{txt}  (_merge==2)

{col 5}matched{col 30}{res}          86,661{txt}  (_merge==3)
{col 5}{hline 41}

{com}. drop _merge
{txt}
{com}. 
. by id, sort: egen sumcemc=sum(cem_matched)
{txt}
{com}. 
. drop cem_matched
{txt}
{com}. 
. gen             controlmc=0
{txt}
{com}. replace         controlmc=1             if (sumcemc>0 & treatc==0)
{txt}(15,710 real changes made)

{com}. codebook        id                                      if controlmc==1

{txt}{hline}
{res}id{right:(unlabeled)}
{txt}{hline}

{col 19}type:  string ({res}str11{txt}), but longest is str9

{col 10}unique values:  {res}105{col 51}{txt}missing "":  {res}0{txt}/{res}15,710

{txt}{col 15}examples:  {res}"59741832"
{col 26}"66385591"
{col 26}"75389707"
{col 26}"82003415"
{txt}
{com}. 
. 
. save "R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta", replace
{txt}file R:\WSV2\TBu_BMa\Subsidies Project\Data Subsidies\Estimation Sample.dta saved

{com}. 
. 
. 
. drop if treataf==1
{txt}(386,437 observations deleted)

{com}. replace treataf=1 if controlma9==1      & country=="Austria"
{txt}(16,369 real changes made)

{com}. replace treataf=1 if controlma10==1 & country=="Austria"
{txt}(17,420 real changes made)

{com}. 
. drop if treata==1
{txt}(5,664 observations deleted)

{com}. replace treata=1  if controlmaw==1  & country=="Austria"
{txt}(3,996 real changes made)

{com}. 
. drop if treathf==1
{txt}(16,863 observations deleted)

{com}. replace treathf=1 if controlmh16==1 & country=="Hungary"
{txt}(12,254 real changes made)

{com}. 
. drop if treath==1
{txt}(15,322 observations deleted)

{com}. replace treath=1  if controlmh15==1 & country=="Hungary"
{txt}(10,327 real changes made)

{com}. 
. drop if treatc==1
{txt}(244,595 observations deleted)

{com}. replace treatc=1  if controlmc==1   & country=="Croatia"
{txt}(4,145 real changes made)

{com}. 
. *+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++  
. 
. ***CLOSE SUBSTITUTES, AUSTRIA, 2009
. preserve
{txt}
{com}. 
. drop if category=="washing machine"
{txt}(572,675 observations deleted)

{com}. egen cmt=group(country month treataf)
{txt}
{com}. 
. xtset id2
{txt}{col 8}panel variable:  {res}id2 (unbalanced)
{txt}
{com}. 
. reghdfe dlogunits i.presub3af9##ib1.treataf i.presub2af9##ib1.treataf i.presub1af9##ib1.treataf i.sub1af9##ib1.treataf i.sub2af9##ib1.treataf i.sub3af9##ib1.treataf i.sub4af9##ib1.treataf i.postsub1af9##ib1.treataf i.postsub2af9##ib1.treataf i.postsub3af9##ib1.treataf  mage mage2 , absorb(id2 cmt) cluster(id) 
{res}{txt}(dropped 151059 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}0bn.treataf{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 13 iterations)
{res}{txt}note: 0.treataf omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   385,476
{txt}Absorbing 2 HDFE groups{col 51}F({res}  22{txt},{res}   8073{txt}){col 67}= {res}      9.49
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4376
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0797
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0004
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}     8,074{txt}{col 51}Root MSE{col 67}= {res}    0.6986

{txt}{ralign 85:(Std. Err. adjusted for {res:8,074} clusters in id)}
{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}          dlogunits{col 21}{c |}      Coef.{col 33}   Std. Err.{col 45}      t{col 53}   P>|t|{col 61}     [95% Con{col 74}f. Interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}1.presub3af9 {c |}{col 21}{res}{space 2} .1441368{col 33}{space 2} .0685083{col 44}{space 1}    2.10{col 53}{space 3}0.035{col 61}{space 4} .0098428{col 74}{space 3} .2784307
{txt}{space 10}0.treataf {c |}{col 21}{res}{space 2}        0{col 33}{txt}  (omitted)
{space 19} {c |}
{space 1}presub3af9#treataf {c |}
{space 15}1 0  {c |}{col 21}{res}{space 2} -.046308{col 33}{space 2} .0738965{col 44}{space 1}   -0.63{col 53}{space 3}0.531{col 61}{space 4}-.1911643{col 74}{space 3} .0985483
{txt}{space 19} {c |}
{space 7}1.presub2af9 {c |}{col 21}{res}{space 2}-.1069283{col 33}{space 2} .0959544{col 44}{space 1}   -1.11{col 53}{space 3}0.265{col 61}{space 4}-.2950238{col 74}{space 3} .0811671
{txt}{space 19} {c |}
{space 1}presub2af9#treataf {c |}
{space 15}1 0  {c |}{col 21}{res}{space 2} .1632245{col 33}{space 2} .1050809{col 44}{space 1}    1.55{col 53}{space 3}0.120{col 61}{space 4}-.0427611{col 74}{space 3} .3692101
{txt}{space 19} {c |}
{space 7}1.presub1af9 {c |}{col 21}{res}{space 2}-.0238484{col 33}{space 2}  .054901{col 44}{space 1}   -0.43{col 53}{space 3}0.664{col 61}{space 4}-.1314684{col 74}{space 3} .0837716
{txt}{space 19} {c |}
{space 1}presub1af9#treataf {c |}
{space 15}1 0  {c |}{col 21}{res}{space 2}-.0061892{col 33}{space 2} .0613509{col 44}{space 1}   -0.10{col 53}{space 3}0.920{col 61}{space 4}-.1264528{col 74}{space 3} .1140745
{txt}{space 19} {c |}
{space 10}1.sub1af9 {c |}{col 21}{res}{space 2} .0240278{col 33}{space 2}  .093246{col 44}{space 1}    0.26{col 53}{space 3}0.797{col 61}{space 4}-.1587584{col 74}{space 3}  .206814
{txt}{space 19} {c |}
{space 4}sub1af9#treataf {c |}
{space 15}1 0  {c |}{col 21}{res}{space 2} .0671564{col 33}{space 2} .1037189{col 44}{space 1}    0.65{col 53}{space 3}0.517{col 61}{space 4}-.1361595{col 74}{space 3} .2704722
{txt}{space 19} {c |}
{space 10}1.sub2af9 {c |}{col 21}{res}{space 2}-.0516787{col 33}{space 2} .0690281{col 44}{space 1}   -0.75{col 53}{space 3}0.454{col 61}{space 4}-.1869915{col 74}{space 3} .0836342
{txt}{space 19} {c |}
{space 4}sub2af9#treataf {c |}
{space 15}1 0  {c |}{col 21}{res}{space 2} .0146853{col 33}{space 2} .0761441{col 44}{space 1}    0.19{col 53}{space 3}0.847{col 61}{space 4}-.1345768{col 74}{space 3} .1639475
{txt}{space 19} {c |}
{space 10}1.sub3af9 {c |}{col 21}{res}{space 2}-.1103597{col 33}{space 2} .1137558{col 44}{space 1}   -0.97{col 53}{space 3}0.332{col 61}{space 4}-.3333503{col 74}{space 3}  .112631
{txt}{space 19} {c |}
{space 4}sub3af9#treataf {c |}
{space 15}1 0  {c |}{col 21}{res}{space 2} .2917253{col 33}{space 2} .1290745{col 44}{space 1}    2.26{col 53}{space 3}0.024{col 61}{space 4}  .038706{col 74}{space 3} .5447446
{txt}{space 19} {c |}
{space 10}1.sub4af9 {c |}{col 21}{res}{space 2} -.088944{col 33}{space 2} .0666135{col 44}{space 1}   -1.34{col 53}{space 3}0.182{col 61}{space 4}-.2195237{col 74}{space 3} .0416357
{txt}{space 19} {c |}
{space 4}sub4af9#treataf {c |}
{space 15}1 0  {c |}{col 21}{res}{space 2} .0659016{col 33}{space 2} .0759974{col 44}{space 1}    0.87{col 53}{space 3}0.386{col 61}{space 4}-.0830728{col 74}{space 3} .2148761
{txt}{space 19} {c |}
{space 6}1.postsub1af9 {c |}{col 21}{res}{space 2} .0555338{col 33}{space 2}  .094194{col 44}{space 1}    0.59{col 53}{space 3}0.555{col 61}{space 4}-.1291107{col 74}{space 3} .2401784
{txt}{space 19} {c |}
postsub1af9#treataf {c |}
{space 15}1 0  {c |}{col 21}{res}{space 2}-.0473082{col 33}{space 2} .1072322{col 44}{space 1}   -0.44{col 53}{space 3}0.659{col 61}{space 4} -.257511{col 74}{space 3} .1628946
{txt}{space 19} {c |}
{space 6}1.postsub2af9 {c |}{col 21}{res}{space 2} .0576656{col 33}{space 2} .1171259{col 44}{space 1}    0.49{col 53}{space 3}0.622{col 61}{space 4}-.1719314{col 74}{space 3} .2872627
{txt}{space 19} {c |}
postsub2af9#treataf {c |}
{space 15}1 0  {c |}{col 21}{res}{space 2}-.0553996{col 33}{space 2} .1301236{col 44}{space 1}   -0.43{col 53}{space 3}0.670{col 61}{space 4}-.3104753{col 74}{space 3} .1996762
{txt}{space 19} {c |}
{space 6}1.postsub3af9 {c |}{col 21}{res}{space 2} .0609691{col 33}{space 2} .0905483{col 44}{space 1}    0.67{col 53}{space 3}0.501{col 61}{space 4}-.1165289{col 74}{space 3} .2384671
{txt}{space 19} {c |}
postsub3af9#treataf {c |}
{space 15}1 0  {c |}{col 21}{res}{space 2} -.037471{col 33}{space 2} .1033313{col 44}{space 1}   -0.36{col 53}{space 3}0.717{col 61}{space 4} -.240027{col 74}{space 3}  .165085
{txt}{space 19} {c |}
{space 15}mage {c |}{col 21}{res}{space 2}-.0029011{col 33}{space 2} .0002751{col 44}{space 1}  -10.55{col 53}{space 3}0.000{col 61}{space 4}-.0034403{col 74}{space 3}-.0023618
{txt}{space 14}mage2 {c |}{col 21}{res}{space 2} .0000213{col 33}{space 2} 2.99e-06{col 44}{space 1}    7.14{col 53}{space 3}0.000{col 61}{space 4} .0000155{col 74}{space 3} .0000272
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .0371711{col 33}{space 2} .0047721{col 44}{space 1}    7.79{col 53}{space 3}0.000{col 61}{space 4} .0278166{col 74}{space 3} .0465255
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}         id2{col 14}{c |}{space 1}   149794{col 27}{space 1}   149794{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}         cmt{col 14}{c |}{space 1}      108{col 27}{space 1}        0{col 39}{result}{space 1}      108{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store close1
{txt}
{com}. 
. esttab   close1 , se star(* 0.10 ** 0.05 *** 0.01) mtitles nogaps b(%8.3f) t(%6.2f)  scalars(N ) order(1.presub2af9 1.presub1af9 1.sub1af9 1.sub2af9 1.sub3af9 1.sub4af9 1.postsub1af9 1.postsub2af9) keep(1.presub2af9 1.presub1af9 1.sub1af9 1.sub2af9 1.sub3af9 1.sub4af9 1.postsub1af9 1.postsub2af9) 
{res}
{txt}{hline 28}
{txt}                      (1)   
{txt}                   close1   
{txt}{hline 28}
{txt}1.presub2af9{res}       -0.107   {txt}
            {res} {ralign 12:{txt:(}0.096{txt:)}}   {txt}
{txt}1.presub1af9{res}       -0.024   {txt}
            {res} {ralign 12:{txt:(}0.055{txt:)}}   {txt}
{txt}1.sub1af9   {res}        0.024   {txt}
            {res} {ralign 12:{txt:(}0.093{txt:)}}   {txt}
{txt}1.sub2af9   {res}       -0.052   {txt}
            {res} {ralign 12:{txt:(}0.069{txt:)}}   {txt}
{txt}1.sub3af9   {res}       -0.110   {txt}
            {res} {ralign 12:{txt:(}0.114{txt:)}}   {txt}
{txt}1.sub4af9   {res}       -0.089   {txt}
            {res} {ralign 12:{txt:(}0.067{txt:)}}   {txt}
{txt}1.postsub1~9{res}        0.056   {txt}
            {res} {ralign 12:{txt:(}0.094{txt:)}}   {txt}
{txt}1.postsub2~9{res}        0.058   {txt}
            {res} {ralign 12:{txt:(}0.117{txt:)}}   {txt}
{txt}{hline 28}
{txt}N           {res}       385476   {txt}
{txt}{hline 28}
{txt}Standard errors in parentheses
{txt}* p<0.10, ** p<0.05, *** p<0.01

{com}. 
. esttab   close1  using "R:\WSV2\TBu_BMa\Subsidies Project\Results\c1.tex", replace  se nostar mtitles nogaps b(%8.3f) t(%6.2f)  scalars(N ) order(1.presub2af9 1.presub1af9 1.sub1af9 1.sub2af9 1.sub3af9 1.sub4af9 1.postsub1af9 1.postsub2af9) keep(1.presub2af9 1.presub1af9 1.sub1af9 1.sub2af9 1.sub3af9 1.sub4af9 1.postsub1af9 1.postsub2af9) 
{res}{txt}(output written to {browse  `"R:\WSV2\TBu_BMa\Subsidies Project\Results\c1.tex"'})

{com}. 
. restore
{txt}
{com}. 
. *+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++  
. ***CLOSE SUBSTITUTES, AUSTRIA, 2010
. 
. preserve
{txt}
{com}. 
. drop if category=="washing machine"
{txt}(572,675 observations deleted)

{com}. egen cmt=group(country month treataf)
{txt}
{com}.  
. xtset id2
{txt}{col 8}panel variable:  {res}id2 (unbalanced)
{txt}
{com}.  
. reghdfe dlogunits i.presub3af10##ib1.treataf i.presub2af10##ib1.treataf i.presub1af10##ib1.treataf i.sub1af10##ib1.treataf i.sub2af10##ib1.treataf i.sub3af10##ib1.treataf i.postsub1af10##ib1.treataf i.postsub2af10##ib1.treataf i.postsub3af10##ib1.treataf  mage mage2 , absorb(id2 cmt) cluster(id)
{res}{txt}(dropped 151059 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}0bn.treataf{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 13 iterations)
{res}{txt}note: 0.treataf omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   385,476
{txt}Absorbing 2 HDFE groups{col 51}F({res}  20{txt},{res}   8073{txt}){col 67}= {res}      9.81
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4376
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0797
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0004
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}     8,074{txt}{col 51}Root MSE{col 67}= {res}    0.6986

{txt}{ralign 86:(Std. Err. adjusted for {res:8,074} clusters in id)}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}           dlogunits{col 22}{c |}      Coef.{col 34}   Std. Err.{col 46}      t{col 54}   P>|t|{col 62}     [95% Con{col 75}f. Interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}1.presub3af10 {c |}{col 22}{res}{space 2} .0135204{col 34}{space 2} .1189867{col 45}{space 1}    0.11{col 54}{space 3}0.910{col 62}{space 4}-.2197243{col 75}{space 3} .2467651
{txt}{space 11}0.treataf {c |}{col 22}{res}{space 2}        0{col 34}{txt}  (omitted)
{space 20} {c |}
{space 1}presub3af10#treataf {c |}
{space 16}1 0  {c |}{col 22}{res}{space 2} .0476969{col 34}{space 2} .1308505{col 45}{space 1}    0.36{col 54}{space 3}0.715{col 62}{space 4}-.2088038{col 75}{space 3} .3041976
{txt}{space 20} {c |}
{space 7}1.presub2af10 {c |}{col 22}{res}{space 2}-.1551787{col 34}{space 2} .0944822{col 45}{space 1}   -1.64{col 54}{space 3}0.101{col 62}{space 4}-.3403881{col 75}{space 3} .0300307
{txt}{space 20} {c |}
{space 1}presub2af10#treataf {c |}
{space 16}1 0  {c |}{col 22}{res}{space 2}  .060392{col 34}{space 2} .1047004{col 45}{space 1}    0.58{col 54}{space 3}0.564{col 62}{space 4}-.1448477{col 75}{space 3} .2656317
{txt}{space 20} {c |}
{space 7}1.presub1af10 {c |}{col 22}{res}{space 2} .1720182{col 34}{space 2} .0970414{col 45}{space 1}    1.77{col 54}{space 3}0.076{col 62}{space 4}-.0182079{col 75}{space 3} .3622443
{txt}{space 20} {c |}
{space 1}presub1af10#treataf {c |}
{space 16}1 0  {c |}{col 22}{res}{space 2}-.1328047{col 34}{space 2} .1086232{col 45}{space 1}   -1.22{col 54}{space 3}0.222{col 62}{space 4}-.3457342{col 75}{space 3} .0801247
{txt}{space 20} {c |}
{space 10}1.sub1af10 {c |}{col 22}{res}{space 2} .0224819{col 34}{space 2} .0915765{col 45}{space 1}    0.25{col 54}{space 3}0.806{col 62}{space 4}-.1570317{col 75}{space 3} .2019955
{txt}{space 20} {c |}
{space 4}sub1af10#treataf {c |}
{space 16}1 0  {c |}{col 22}{res}{space 2}-.0793668{col 34}{space 2} .1015951{col 45}{space 1}   -0.78{col 54}{space 3}0.435{col 62}{space 4}-.2785194{col 75}{space 3} .1197858
{txt}{space 20} {c |}
{space 10}1.sub2af10 {c |}{col 22}{res}{space 2}-.0218829{col 34}{space 2} .1119564{col 45}{space 1}   -0.20{col 54}{space 3}0.845{col 62}{space 4}-.2413463{col 75}{space 3} .1975805
{txt}{space 20} {c |}
{space 4}sub2af10#treataf {c |}
{space 16}1 0  {c |}{col 22}{res}{space 2} .1425808{col 34}{space 2} .1246162{col 45}{space 1}    1.14{col 54}{space 3}0.253{col 62}{space 4}-.1016991{col 75}{space 3} .3868607
{txt}{space 20} {c |}
{space 10}1.sub3af10 {c |}{col 22}{res}{space 2}-.0580437{col 34}{space 2} .1043945{col 45}{space 1}   -0.56{col 54}{space 3}0.578{col 62}{space 4}-.2626839{col 75}{space 3} .1465965
{txt}{space 20} {c |}
{space 4}sub3af10#treataf {c |}
{space 16}1 0  {c |}{col 22}{res}{space 2} .0646772{col 34}{space 2} .1138702{col 45}{space 1}    0.57{col 54}{space 3}0.570{col 62}{space 4}-.1585377{col 75}{space 3} .2878921
{txt}{space 20} {c |}
{space 6}1.postsub1af10 {c |}{col 22}{res}{space 2}-.0087193{col 34}{space 2} .1058431{col 45}{space 1}   -0.08{col 54}{space 3}0.934{col 62}{space 4}-.2161992{col 75}{space 3} .1987605
{txt}{space 20} {c |}
postsub1af10#treataf {c |}
{space 16}1 0  {c |}{col 22}{res}{space 2}-.0334722{col 34}{space 2} .1193175{col 45}{space 1}   -0.28{col 54}{space 3}0.779{col 62}{space 4}-.2673654{col 75}{space 3} .2004209
{txt}{space 20} {c |}
{space 6}1.postsub2af10 {c |}{col 22}{res}{space 2}-.1298842{col 34}{space 2}  .101927{col 45}{space 1}   -1.27{col 54}{space 3}0.203{col 62}{space 4}-.3296875{col 75}{space 3}  .069919
{txt}{space 20} {c |}
postsub2af10#treataf {c |}
{space 16}1 0  {c |}{col 22}{res}{space 2}-.0096444{col 34}{space 2} .1129409{col 45}{space 1}   -0.09{col 54}{space 3}0.932{col 62}{space 4}-.2310378{col 75}{space 3} .2117489
{txt}{space 20} {c |}
{space 6}1.postsub3af10 {c |}{col 22}{res}{space 2} .1827949{col 34}{space 2} .1091416{col 45}{space 1}    1.67{col 54}{space 3}0.094{col 62}{space 4}-.0311507{col 75}{space 3} .3967405
{txt}{space 20} {c |}
postsub3af10#treataf {c |}
{space 16}1 0  {c |}{col 22}{res}{space 2}-.1641686{col 34}{space 2} .1218669{col 45}{space 1}   -1.35{col 54}{space 3}0.178{col 62}{space 4}-.4030592{col 75}{space 3}  .074722
{txt}{space 20} {c |}
{space 16}mage {c |}{col 22}{res}{space 2}-.0028942{col 34}{space 2}  .000275{col 45}{space 1}  -10.53{col 54}{space 3}0.000{col 62}{space 4}-.0034331{col 75}{space 3}-.0023552
{txt}{space 15}mage2 {c |}{col 22}{res}{space 2} .0000213{col 34}{space 2} 2.99e-06{col 45}{space 1}    7.11{col 54}{space 3}0.000{col 62}{space 4} .0000154{col 75}{space 3} .0000271
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} .0375717{col 34}{space 2} .0047643{col 45}{space 1}    7.89{col 54}{space 3}0.000{col 62}{space 4} .0282324{col 75}{space 3}  .046911
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}         id2{col 14}{c |}{space 1}   149794{col 27}{space 1}   149794{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}         cmt{col 14}{c |}{space 1}      108{col 27}{space 1}        0{col 39}{result}{space 1}      108{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store close2
{txt}
{com}. 
. esttab   close2, se star(* 0.10 ** 0.05 *** 0.01) mtitles nogaps b(%8.3f) t(%6.2f)  scalars(N ) order(1.presub2af10 1.presub1af10 1.sub1af10 1.sub2af10 1.sub3af10 1.postsub1af10 1.postsub2af10) keep(1.presub2af10 1.presub1af10 1.sub1af10 1.sub2af10 1.sub3af10 1.postsub1af10 1.postsub2af10)
{res}
{txt}{hline 28}
{txt}                      (1)   
{txt}                   close2   
{txt}{hline 28}
{txt}1.presub2~10{res}       -0.155   {txt}
            {res} {ralign 12:{txt:(}0.094{txt:)}}   {txt}
{txt}1.presub1~10{res}        0.172*  {txt}
            {res} {ralign 12:{txt:(}0.097{txt:)}}   {txt}
{txt}1.sub1af10  {res}        0.022   {txt}
            {res} {ralign 12:{txt:(}0.092{txt:)}}   {txt}
{txt}1.sub2af10  {res}       -0.022   {txt}
            {res} {ralign 12:{txt:(}0.112{txt:)}}   {txt}
{txt}1.sub3af10  {res}       -0.058   {txt}
            {res} {ralign 12:{txt:(}0.104{txt:)}}   {txt}
{txt}1.postsub1~0{res}       -0.009   {txt}
            {res} {ralign 12:{txt:(}0.106{txt:)}}   {txt}
{txt}1.postsub2~0{res}       -0.130   {txt}
            {res} {ralign 12:{txt:(}0.102{txt:)}}   {txt}
{txt}{hline 28}
{txt}N           {res}       385476   {txt}
{txt}{hline 28}
{txt}Standard errors in parentheses
{txt}* p<0.10, ** p<0.05, *** p<0.01

{com}. 
. esttab   close2  using "R:\WSV2\TBu_BMa\Subsidies Project\Results\c2.tex", replace  se nostar mtitles nogaps b(%8.3f) t(%6.2f)  scalars(N ) order(1.presub2af10 1.presub1af10 1.sub1af10 1.sub2af10 1.sub3af10 1.postsub1af10 1.postsub2af10) keep(1.presub2af10 1.presub1af10 1.sub1af10 1.sub2af10 1.sub3af10 1.postsub1af10 1.postsub2af10) 
{res}{txt}(output written to {browse  `"R:\WSV2\TBu_BMa\Subsidies Project\Results\c2.tex"'})

{com}. 
. restore
{txt}
{com}. 
. *+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++  
. ***CLOSE SUBSTITUTES, AUSTRIA, 2010, WM
. 
. preserve
{txt}
{com}. 
. keep if category=="washing machine"
{txt}(1,271,805 observations deleted)

{com}. 
. egen cmt=group(country month treata)
{txt}
{com}. 
. xtset id2
{txt}{col 8}panel variable:  {res}id2 (unbalanced)
{txt}
{com}. 
. reghdfe dlogunits i.presub3a##ib1.treata i.presub2a##ib1.treata i.presub1a##ib1.treata i.sub1a##ib1.treata i.sub2a##ib1.treata i.postsub1a##ib1.treata i.postsub2a##ib1.treata i.postsub3a##ib1.treata  mage mage2 , absorb(id2 cmt) cluster(id) 
{res}{txt}(dropped 68180 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}0bn.treata{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 14 iterations)
{res}{txt}note: 0.treata omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   191,982
{txt}Absorbing 2 HDFE groups{col 51}F({res}  18{txt},{res}   4386{txt}){col 67}= {res}      5.22
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4478
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0743
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0005
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}     4,387{txt}{col 51}Root MSE{col 67}= {res}    0.7178

{txt}{ralign 82:(Std. Err. adjusted for {res:4,387} clusters in id)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}       dlogunits{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}1.presub3a {c |}{col 18}{res}{space 2} .1825482{col 30}{space 2} .3163585{col 41}{space 1}    0.58{col 50}{space 3}0.564{col 58}{space 4}-.4376743{col 71}{space 3} .8027707
{txt}{space 8}0.treata {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 16} {c |}
{space 1}presub3a#treata {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2}-.1253392{col 30}{space 2} .3259003{col 41}{space 1}   -0.38{col 50}{space 3}0.701{col 58}{space 4}-.7642684{col 71}{space 3} .5135901
{txt}{space 16} {c |}
{space 6}1.presub2a {c |}{col 18}{res}{space 2} .2918421{col 30}{space 2} .2061586{col 41}{space 1}    1.42{col 50}{space 3}0.157{col 58}{space 4}-.1123328{col 71}{space 3}  .696017
{txt}{space 16} {c |}
{space 1}presub2a#treata {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2}-.2505919{col 30}{space 2} .2201383{col 41}{space 1}   -1.14{col 50}{space 3}0.255{col 58}{space 4}-.6821741{col 71}{space 3} .1809903
{txt}{space 16} {c |}
{space 6}1.presub1a {c |}{col 18}{res}{space 2}-.1562243{col 30}{space 2} .2653808{col 41}{space 1}   -0.59{col 50}{space 3}0.556{col 58}{space 4}-.6765047{col 71}{space 3}  .364056
{txt}{space 16} {c |}
{space 1}presub1a#treata {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2} .1335516{col 30}{space 2} .2734564{col 41}{space 1}    0.49{col 50}{space 3}0.625{col 58}{space 4} -.402561{col 71}{space 3} .6696642
{txt}{space 16} {c |}
{space 9}1.sub1a {c |}{col 18}{res}{space 2} .1648605{col 30}{space 2} .2110185{col 41}{space 1}    0.78{col 50}{space 3}0.435{col 58}{space 4}-.2488423{col 71}{space 3} .5785634
{txt}{space 16} {c |}
{space 4}sub1a#treata {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2}-.2982846{col 30}{space 2} .2231543{col 41}{space 1}   -1.34{col 50}{space 3}0.181{col 58}{space 4}-.7357798{col 71}{space 3} .1392105
{txt}{space 16} {c |}
{space 9}1.sub2a {c |}{col 18}{res}{space 2}-.1898357{col 30}{space 2} .1769452{col 41}{space 1}   -1.07{col 50}{space 3}0.283{col 58}{space 4}-.5367378{col 71}{space 3} .1570663
{txt}{space 16} {c |}
{space 4}sub2a#treata {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2} .1254237{col 30}{space 2}  .190488{col 41}{space 1}    0.66{col 50}{space 3}0.510{col 58}{space 4} -.248029{col 71}{space 3} .4988763
{txt}{space 16} {c |}
{space 5}1.postsub1a {c |}{col 18}{res}{space 2}  .005076{col 30}{space 2}  .259968{col 41}{space 1}    0.02{col 50}{space 3}0.984{col 58}{space 4}-.5045927{col 71}{space 3} .5147446
{txt}{space 16} {c |}
postsub1a#treata {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2} .2282258{col 30}{space 2} .2691415{col 41}{space 1}    0.85{col 50}{space 3}0.396{col 58}{space 4}-.2994274{col 71}{space 3}  .755879
{txt}{space 16} {c |}
{space 5}1.postsub2a {c |}{col 18}{res}{space 2}-.2592171{col 30}{space 2} .2802998{col 41}{space 1}   -0.92{col 50}{space 3}0.355{col 58}{space 4}-.8087463{col 71}{space 3} .2903121
{txt}{space 16} {c |}
postsub2a#treata {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2} .2769608{col 30}{space 2} .2891418{col 41}{space 1}    0.96{col 50}{space 3}0.338{col 58}{space 4}-.2899032{col 71}{space 3} .8438248
{txt}{space 16} {c |}
{space 5}1.postsub3a {c |}{col 18}{res}{space 2}-.1475203{col 30}{space 2} .1911411{col 41}{space 1}   -0.77{col 50}{space 3}0.440{col 58}{space 4}-.5222533{col 71}{space 3} .2272127
{txt}{space 16} {c |}
postsub3a#treata {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2} .0430354{col 30}{space 2} .2019244{col 41}{space 1}    0.21{col 50}{space 3}0.831{col 58}{space 4}-.3528383{col 71}{space 3} .4389091
{txt}{space 16} {c |}
{space 12}mage {c |}{col 18}{res}{space 2}-.0033985{col 30}{space 2} .0005232{col 41}{space 1}   -6.50{col 50}{space 3}0.000{col 58}{space 4}-.0044242{col 71}{space 3}-.0023729
{txt}{space 11}mage2 {c |}{col 18}{res}{space 2} .0000279{col 30}{space 2} 7.02e-06{col 41}{space 1}    3.97{col 50}{space 3}0.000{col 58}{space 4} .0000141{col 71}{space 3} .0000416
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0304967{col 30}{space 2} .0079441{col 41}{space 1}    3.84{col 50}{space 3}0.000{col 58}{space 4} .0149223{col 71}{space 3} .0460711
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}         id2{col 14}{c |}{space 1}    77338{col 27}{space 1}    77338{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}         cmt{col 14}{c |}{space 1}      108{col 27}{space 1}        0{col 39}{result}{space 1}      108{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store close3
{txt}
{com}. 
. esttab   close3, se star(* 0.10 ** 0.05 *** 0.01) mtitles nogaps b(%8.3f) t(%6.2f)  scalars(N ) order(1.presub2a 1.presub1a 1.sub1a 1.sub2a 1.postsub1a 1.postsub2a) keep(1.presub2a 1.presub1a 1.sub1a 1.sub2a 1.postsub1a 1.postsub2a) 
{res}
{txt}{hline 28}
{txt}                      (1)   
{txt}                   close3   
{txt}{hline 28}
{txt}1.presub2a  {res}        0.292   {txt}
            {res} {ralign 12:{txt:(}0.206{txt:)}}   {txt}
{txt}1.presub1a  {res}       -0.156   {txt}
            {res} {ralign 12:{txt:(}0.265{txt:)}}   {txt}
{txt}1.sub1a     {res}        0.165   {txt}
            {res} {ralign 12:{txt:(}0.211{txt:)}}   {txt}
{txt}1.sub2a     {res}       -0.190   {txt}
            {res} {ralign 12:{txt:(}0.177{txt:)}}   {txt}
{txt}1.postsub1a {res}        0.005   {txt}
            {res} {ralign 12:{txt:(}0.260{txt:)}}   {txt}
{txt}1.postsub2a {res}       -0.259   {txt}
            {res} {ralign 12:{txt:(}0.280{txt:)}}   {txt}
{txt}{hline 28}
{txt}N           {res}       191982   {txt}
{txt}{hline 28}
{txt}Standard errors in parentheses
{txt}* p<0.10, ** p<0.05, *** p<0.01

{com}. 
. esttab   close3  using "R:\WSV2\TBu_BMa\Subsidies Project\Results\c3.tex", replace se nostar mtitles nogaps b(%8.3f) t(%6.2f)  scalars(N ) order(1.presub2a 1.presub1a 1.sub1a 1.sub2a 1.postsub1a 1.postsub2a) keep(1.presub2a 1.presub1a 1.sub1a 1.sub2a 1.postsub1a 1.postsub2a)  
{res}{txt}(output written to {browse  `"R:\WSV2\TBu_BMa\Subsidies Project\Results\c3.tex"'})

{com}. 
. restore
{txt}
{com}. 
. 
. *+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++  
. ***CLOSE SUBSTITUTES, HUNGARY, 2015
. 
. preserve
{txt}
{com}. 
. keep if category=="washing machine"
{txt}(1,271,805 observations deleted)

{com}. 
. egen cmt=group(country month treath)
{txt}
{com}. 
. xtset id2
{txt}{col 8}panel variable:  {res}id2 (unbalanced)
{txt}
{com}. 
. 
. reghdfe dlogunits i.presub3h##ib1.treath i.presub2h##ib1.treath i.presub1h##ib1.treath i.sub1h##ib1.treath i.sub2h##ib1.treath i.sub3h##ib1.treath i.sub4h##ib1.treath i.postsub1h##ib1.treath i.postsub2h##ib1.treath i.postsub3h##ib1.treath mage mage2  if country!="Croatia", absorb(id2 cmt) cluster(id) 
{res}{txt}(dropped 70775 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}0bn.treath{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 13 iterations)
{res}{txt}note: 0.treath omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   168,734
{txt}Absorbing 2 HDFE groups{col 51}F({res}  22{txt},{res}   4086{txt}){col 67}= {res}      3.97
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4626
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0786
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0005
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}     4,087{txt}{col 51}Root MSE{col 67}= {res}    0.7242

{txt}{ralign 82:(Std. Err. adjusted for {res:4,087} clusters in id)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}       dlogunits{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}1.presub3h {c |}{col 18}{res}{space 2} .2715906{col 30}{space 2} .3376571{col 41}{space 1}    0.80{col 50}{space 3}0.421{col 58}{space 4}-.3904013{col 71}{space 3} .9335824
{txt}{space 8}0.treath {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 16} {c |}
{space 1}presub3h#treath {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2}-.3581064{col 30}{space 2} .3668811{col 41}{space 1}   -0.98{col 50}{space 3}0.329{col 58}{space 4}-1.077393{col 71}{space 3} .3611804
{txt}{space 16} {c |}
{space 6}1.presub2h {c |}{col 18}{res}{space 2} .1837032{col 30}{space 2} .2300289{col 41}{space 1}    0.80{col 50}{space 3}0.425{col 58}{space 4}-.2672788{col 71}{space 3} .6346852
{txt}{space 16} {c |}
{space 1}presub2h#treath {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2}-.0309859{col 30}{space 2} .2637436{col 41}{space 1}   -0.12{col 50}{space 3}0.906{col 58}{space 4} -.548067{col 71}{space 3} .4860951
{txt}{space 16} {c |}
{space 6}1.presub1h {c |}{col 18}{res}{space 2}-.3000151{col 30}{space 2} .2032396{col 41}{space 1}   -1.48{col 50}{space 3}0.140{col 58}{space 4}-.6984754{col 71}{space 3} .0984452
{txt}{space 16} {c |}
{space 1}presub1h#treath {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2} .4963595{col 30}{space 2} .2712465{col 41}{space 1}    1.83{col 50}{space 3}0.067{col 58}{space 4}-.0354313{col 71}{space 3}  1.02815
{txt}{space 16} {c |}
{space 9}1.sub1h {c |}{col 18}{res}{space 2} .0466115{col 30}{space 2}  .245853{col 41}{space 1}    0.19{col 50}{space 3}0.850{col 58}{space 4}-.4353944{col 71}{space 3} .5286173
{txt}{space 16} {c |}
{space 4}sub1h#treath {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2} .0281153{col 30}{space 2} .3011564{col 41}{space 1}    0.09{col 50}{space 3}0.926{col 58}{space 4}-.5623153{col 71}{space 3} .6185459
{txt}{space 16} {c |}
{space 9}1.sub2h {c |}{col 18}{res}{space 2}  .223909{col 30}{space 2} .6575114{col 41}{space 1}    0.34{col 50}{space 3}0.733{col 58}{space 4}-1.065171{col 71}{space 3} 1.512989
{txt}{space 16} {c |}
{space 4}sub2h#treath {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2}-.1671912{col 30}{space 2} .6716004{col 41}{space 1}   -0.25{col 50}{space 3}0.803{col 58}{space 4}-1.483894{col 71}{space 3} 1.149511
{txt}{space 16} {c |}
{space 9}1.sub3h {c |}{col 18}{res}{space 2}-.2807875{col 30}{space 2} .2620471{col 41}{space 1}   -1.07{col 50}{space 3}0.284{col 58}{space 4}-.7945426{col 71}{space 3} .2329677
{txt}{space 16} {c |}
{space 4}sub3h#treath {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2} .2296394{col 30}{space 2} .2833143{col 41}{space 1}    0.81{col 50}{space 3}0.418{col 58}{space 4} -.325811{col 71}{space 3} .7850897
{txt}{space 16} {c |}
{space 9}1.sub4h {c |}{col 18}{res}{space 2} .3416232{col 30}{space 2} .1887142{col 41}{space 1}    1.81{col 50}{space 3}0.070{col 58}{space 4}-.0283594{col 71}{space 3} .7116058
{txt}{space 16} {c |}
{space 4}sub4h#treath {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2}-.5255017{col 30}{space 2} .2365803{col 41}{space 1}   -2.22{col 50}{space 3}0.026{col 58}{space 4}-.9893279{col 71}{space 3}-.0616754
{txt}{space 16} {c |}
{space 5}1.postsub1h {c |}{col 18}{res}{space 2}-.2158831{col 30}{space 2} .3408894{col 41}{space 1}   -0.63{col 50}{space 3}0.527{col 58}{space 4} -.884212{col 71}{space 3} .4524458
{txt}{space 16} {c |}
postsub1h#treath {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2} .4318988{col 30}{space 2} .3698613{col 41}{space 1}    1.17{col 50}{space 3}0.243{col 58}{space 4}-.2932308{col 71}{space 3} 1.157029
{txt}{space 16} {c |}
{space 5}1.postsub2h {c |}{col 18}{res}{space 2} -.160389{col 30}{space 2} .2183701{col 41}{space 1}   -0.73{col 50}{space 3}0.463{col 58}{space 4}-.5885134{col 71}{space 3} .2677354
{txt}{space 16} {c |}
postsub2h#treath {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2} -.261315{col 30}{space 2} .2711513{col 41}{space 1}   -0.96{col 50}{space 3}0.335{col 58}{space 4}-.7929193{col 71}{space 3} .2702893
{txt}{space 16} {c |}
{space 5}1.postsub3h {c |}{col 18}{res}{space 2}-.0696109{col 30}{space 2} .3123716{col 41}{space 1}   -0.22{col 50}{space 3}0.824{col 58}{space 4}-.6820294{col 71}{space 3} .5428075
{txt}{space 16} {c |}
postsub3h#treath {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2} .2865005{col 30}{space 2} .3486583{col 41}{space 1}    0.82{col 50}{space 3}0.411{col 58}{space 4}-.3970597{col 71}{space 3} .9700608
{txt}{space 16} {c |}
{space 12}mage {c |}{col 18}{res}{space 2}-.0032245{col 30}{space 2}  .000544{col 41}{space 1}   -5.93{col 50}{space 3}0.000{col 58}{space 4}-.0042911{col 71}{space 3} -.002158
{txt}{space 11}mage2 {c |}{col 18}{res}{space 2}  .000025{col 30}{space 2} 6.65e-06{col 41}{space 1}    3.75{col 50}{space 3}0.000{col 58}{space 4} .0000119{col 71}{space 3}  .000038
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0264247{col 30}{space 2}  .008762{col 41}{space 1}    3.02{col 50}{space 3}0.003{col 58}{space 4} .0092464{col 71}{space 3}  .043603
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}         id2{col 14}{c |}{space 1}    70204{col 27}{space 1}    70204{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}         cmt{col 14}{c |}{space 1}       96{col 27}{space 1}        0{col 39}{result}{space 1}       96{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store close4
{txt}
{com}. 
. esttab   close4 , se star(* 0.10 ** 0.05 *** 0.01) mtitles nogaps b(%8.3f) t(%6.2f)  scalars(N ) order(1.presub2h 1.presub1h 1.sub1h 1.sub2h 1.sub3h 1.sub4h 1.postsub1h 1.postsub2h) keep(1.presub2h 1.presub1h 1.sub1h 1.sub2h 1.sub3h 1.sub4h 1.postsub1h 1.postsub2h) 
{res}
{txt}{hline 28}
{txt}                      (1)   
{txt}                   close4   
{txt}{hline 28}
{txt}1.presub2h  {res}        0.184   {txt}
            {res} {ralign 12:{txt:(}0.230{txt:)}}   {txt}
{txt}1.presub1h  {res}       -0.300   {txt}
            {res} {ralign 12:{txt:(}0.203{txt:)}}   {txt}
{txt}1.sub1h     {res}        0.047   {txt}
            {res} {ralign 12:{txt:(}0.246{txt:)}}   {txt}
{txt}1.sub2h     {res}        0.224   {txt}
            {res} {ralign 12:{txt:(}0.658{txt:)}}   {txt}
{txt}1.sub3h     {res}       -0.281   {txt}
            {res} {ralign 12:{txt:(}0.262{txt:)}}   {txt}
{txt}1.sub4h     {res}        0.342*  {txt}
            {res} {ralign 12:{txt:(}0.189{txt:)}}   {txt}
{txt}1.postsub1h {res}       -0.216   {txt}
            {res} {ralign 12:{txt:(}0.341{txt:)}}   {txt}
{txt}1.postsub2h {res}       -0.160   {txt}
            {res} {ralign 12:{txt:(}0.218{txt:)}}   {txt}
{txt}{hline 28}
{txt}N           {res}       168734   {txt}
{txt}{hline 28}
{txt}Standard errors in parentheses
{txt}* p<0.10, ** p<0.05, *** p<0.01

{com}. 
. esttab   close4  using "R:\WSV2\TBu_BMa\Subsidies Project\Results\c4.tex" ,replace  se nostar mtitles nogaps b(%8.3f) t(%6.2f)  scalars(N ) order(1.presub2h 1.presub1h 1.sub1h 1.sub2h 1.sub3h 1.sub4h 1.postsub1h 1.postsub2h) keep(1.presub2h 1.presub1h 1.sub1h 1.sub2h 1.sub3h 1.sub4h 1.postsub1h 1.postsub2h) 
{res}{txt}(note: file R:\WSV2\TBu_BMa\Subsidies Project\Results\c4.tex not found)
(output written to {browse  `"R:\WSV2\TBu_BMa\Subsidies Project\Results\c4.tex"'})

{com}. 
. 
. restore
{txt}
{com}. 
. *+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++  
. ***CLOSE SUBSTITUTES, HUNGARY, 2016
. 
. preserve
{txt}
{com}. drop if category=="washing machine"
{txt}(572,675 observations deleted)

{com}. egen cmt=group(country month treathf)
{txt}
{com}. 
. xtset id2
{txt}{col 8}panel variable:  {res}id2 (unbalanced)
{txt}
{com}. 
. reghdfe dlogunits i.presub3hf##ib1.treathf i.presub2hf##ib1.treathf i.presub1hf##ib1.treathf i.sub1hf##ib1.treathf i.sub2hf##ib1.treathf i.sub3hf##ib1.treathf i.sub4hf##ib1.treathf i.postsub1hf##ib1.treathf  mage mage2 , absorb(id2 cmt) cluster(id)
{res}{txt}(dropped 151059 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}0bn.treathf{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 13 iterations)
{res}{txt}note: 0.treathf omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   385,476
{txt}Absorbing 2 HDFE groups{col 51}F({res}  18{txt},{res}   8073{txt}){col 67}= {res}     12.09
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4376
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0797
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0004
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}     8,074{txt}{col 51}Root MSE{col 67}= {res}    0.6986

{txt}{ralign 84:(Std. Err. adjusted for {res:8,074} clusters in id)}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}         dlogunits{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}1.presub3hf {c |}{col 20}{res}{space 2}-.2456183{col 32}{space 2}  .163768{col 43}{space 1}   -1.50{col 52}{space 3}0.134{col 60}{space 4}-.5666458{col 73}{space 3} .0754092
{txt}{space 9}0.treathf {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 1}presub3hf#treathf {c |}
{space 14}1 0  {c |}{col 20}{res}{space 2} .1234779{col 32}{space 2} .2004185{col 43}{space 1}    0.62{col 52}{space 3}0.538{col 60}{space 4} -.269394{col 73}{space 3} .5163498
{txt}{space 18} {c |}
{space 7}1.presub2hf {c |}{col 20}{res}{space 2} .0065553{col 32}{space 2} .1437262{col 43}{space 1}    0.05{col 52}{space 3}0.964{col 60}{space 4}-.2751851{col 73}{space 3} .2882957
{txt}{space 18} {c |}
{space 1}presub2hf#treathf {c |}
{space 14}1 0  {c |}{col 20}{res}{space 2}-.1728468{col 32}{space 2} .2321881{col 43}{space 1}   -0.74{col 52}{space 3}0.457{col 60}{space 4}-.6279954{col 73}{space 3} .2823018
{txt}{space 18} {c |}
{space 7}1.presub1hf {c |}{col 20}{res}{space 2}-.2844029{col 32}{space 2} .1315626{col 43}{space 1}   -2.16{col 52}{space 3}0.031{col 60}{space 4}-.5422996{col 73}{space 3}-.0265062
{txt}{space 18} {c |}
{space 1}presub1hf#treathf {c |}
{space 14}1 0  {c |}{col 20}{res}{space 2} .7121154{col 32}{space 2}  .315871{col 43}{space 1}    2.25{col 52}{space 3}0.024{col 60}{space 4} .0929267{col 73}{space 3} 1.331304
{txt}{space 18} {c |}
{space 10}1.sub1hf {c |}{col 20}{res}{space 2} .2460382{col 32}{space 2} .1271531{col 43}{space 1}    1.93{col 52}{space 3}0.053{col 60}{space 4}-.0032147{col 73}{space 3} .4952911
{txt}{space 18} {c |}
{space 4}sub1hf#treathf {c |}
{space 14}1 0  {c |}{col 20}{res}{space 2} .0058324{col 32}{space 2} .3489685{col 43}{space 1}    0.02{col 52}{space 3}0.987{col 60}{space 4}-.6782359{col 73}{space 3} .6899006
{txt}{space 18} {c |}
{space 10}1.sub2hf {c |}{col 20}{res}{space 2} -.057109{col 32}{space 2}  .110484{col 43}{space 1}   -0.52{col 52}{space 3}0.605{col 60}{space 4}-.2736862{col 73}{space 3} .1594681
{txt}{space 18} {c |}
{space 4}sub2hf#treathf {c |}
{space 14}1 0  {c |}{col 20}{res}{space 2}-.2464521{col 32}{space 2} .2117367{col 43}{space 1}   -1.16{col 52}{space 3}0.244{col 60}{space 4}-.6615107{col 73}{space 3} .1686065
{txt}{space 18} {c |}
{space 10}1.sub3hf {c |}{col 20}{res}{space 2} .1692646{col 32}{space 2} .1996533{col 43}{space 1}    0.85{col 52}{space 3}0.397{col 60}{space 4}-.2221074{col 73}{space 3} .5606366
{txt}{space 18} {c |}
{space 4}sub3hf#treathf {c |}
{space 14}1 0  {c |}{col 20}{res}{space 2} .4098597{col 32}{space 2} .3240396{col 43}{space 1}    1.26{col 52}{space 3}0.206{col 60}{space 4}-.2253415{col 73}{space 3} 1.045061
{txt}{space 18} {c |}
{space 10}1.sub4hf {c |}{col 20}{res}{space 2}-.0892695{col 32}{space 2} .1522017{col 43}{space 1}   -0.59{col 52}{space 3}0.558{col 60}{space 4}-.3876239{col 73}{space 3}  .209085
{txt}{space 18} {c |}
{space 4}sub4hf#treathf {c |}
{space 14}1 0  {c |}{col 20}{res}{space 2} .3696828{col 32}{space 2} .2048453{col 43}{space 1}    1.80{col 52}{space 3}0.071{col 60}{space 4}-.0318669{col 73}{space 3} .7712324
{txt}{space 18} {c |}
{space 6}1.postsub1hf {c |}{col 20}{res}{space 2} .3206579{col 32}{space 2} .1984531{col 43}{space 1}    1.62{col 52}{space 3}0.106{col 60}{space 4}-.0683613{col 73}{space 3}  .709677
{txt}{space 18} {c |}
postsub1hf#treathf {c |}
{space 14}1 0  {c |}{col 20}{res}{space 2}-.2531022{col 32}{space 2} .2833767{col 43}{space 1}   -0.89{col 52}{space 3}0.372{col 60}{space 4}-.8085936{col 73}{space 3} .3023891
{txt}{space 18} {c |}
{space 14}mage {c |}{col 20}{res}{space 2}-.0029117{col 32}{space 2} .0002755{col 43}{space 1}  -10.57{col 52}{space 3}0.000{col 60}{space 4}-.0034518{col 73}{space 3}-.0023717
{txt}{space 13}mage2 {c |}{col 20}{res}{space 2} .0000215{col 32}{space 2} 3.01e-06{col 43}{space 1}    7.15{col 52}{space 3}0.000{col 60}{space 4} .0000156{col 73}{space 3} .0000274
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} .0377314{col 32}{space 2} .0047656{col 43}{space 1}    7.92{col 52}{space 3}0.000{col 60}{space 4} .0283895{col 73}{space 3} .0470733
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}         id2{col 14}{c |}{space 1}   149794{col 27}{space 1}   149794{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}         cmt{col 14}{c |}{space 1}      108{col 27}{space 1}        0{col 39}{result}{space 1}      108{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store close5
{txt}
{com}. 
. esttab   close5 , se star(* 0.10 ** 0.05 *** 0.01) mtitles nogaps b(%8.3f) t(%6.2f)  scalars(N ) order(1.presub2hf 1.presub1hf 1.sub1hf 1.sub2hf 1.sub3hf 1.sub4hf 1.postsub1hf) keep(1.presub2hf 1.presub1hf 1.sub1hf 1.sub2hf 1.sub3hf 1.sub4hf 1.postsub1hf) 
{res}
{txt}{hline 28}
{txt}                      (1)   
{txt}                   close5   
{txt}{hline 28}
{txt}1.presub2hf {res}        0.007   {txt}
            {res} {ralign 12:{txt:(}0.144{txt:)}}   {txt}
{txt}1.presub1hf {res}       -0.284** {txt}
            {res} {ralign 12:{txt:(}0.132{txt:)}}   {txt}
{txt}1.sub1hf    {res}        0.246*  {txt}
            {res} {ralign 12:{txt:(}0.127{txt:)}}   {txt}
{txt}1.sub2hf    {res}       -0.057   {txt}
            {res} {ralign 12:{txt:(}0.110{txt:)}}   {txt}
{txt}1.sub3hf    {res}        0.169   {txt}
            {res} {ralign 12:{txt:(}0.200{txt:)}}   {txt}
{txt}1.sub4hf    {res}       -0.089   {txt}
            {res} {ralign 12:{txt:(}0.152{txt:)}}   {txt}
{txt}1.postsub1hf{res}        0.321   {txt}
            {res} {ralign 12:{txt:(}0.198{txt:)}}   {txt}
{txt}{hline 28}
{txt}N           {res}       385476   {txt}
{txt}{hline 28}
{txt}Standard errors in parentheses
{txt}* p<0.10, ** p<0.05, *** p<0.01

{com}. 
. esttab   close5  using "R:\WSV2\TBu_BMa\Subsidies Project\Results\c5.tex" ,replace  se nostar mtitles nogaps b(%8.3f) t(%6.2f)  scalars(N ) order(1.presub2hf 1.presub1hf 1.sub1hf 1.sub2hf 1.sub3hf 1.sub4hf 1.postsub1hf) keep(1.presub2hf 1.presub1hf 1.sub1hf 1.sub2hf 1.sub3hf 1.sub4hf 1.postsub1hf) 
{res}{txt}(output written to {browse  `"R:\WSV2\TBu_BMa\Subsidies Project\Results\c5.tex"'})

{com}. 
. restore
{txt}
{com}. 
. *+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++  
. ***CLOSE SUBSTITUTES, CROATIA, 2015
. preserve
{txt}
{com}. keep if category=="washing machine"
{txt}(1,271,805 observations deleted)

{com}. 
. egen cmt=group(country month treatc)
{txt}
{com}. 
. xtset id2
{txt}{col 8}panel variable:  {res}id2 (unbalanced)
{txt}
{com}. 
. 
. reghdfe dlogunits i.presub3c##ib1.treatc i.presub2c##ib1.treatc i.presub1c##ib1.treatc i.sub1c##ib1.treatc i.postsub1c##ib1.treatc i.postsub2c##ib1.treatc i.postsub3c##ib1.treatc i.postsub4c##ib1.treatc i.postsub5c##ib1.treatc i.postsub6c##ib1.treatc  i.postsub7c##ib1.treatc mage mage2  if country!="Hungary" , absorb (id2 cmt) cluster(id)
{res}{txt}(dropped 74246 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}0bn.treatc{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 14 iterations)
{res}{txt}note: 0.treatc omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   153,131
{txt}Absorbing 2 HDFE groups{col 51}F({res}  24{txt},{res}   3867{txt}){col 67}= {res}      3.99
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4699
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0711
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0007
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}     3,868{txt}{col 51}Root MSE{col 67}= {res}    0.7187

{txt}{ralign 82:(Std. Err. adjusted for {res:3,868} clusters in id)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}       dlogunits{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}1.presub3c {c |}{col 18}{res}{space 2}-.0255067{col 30}{space 2} .2209872{col 41}{space 1}   -0.12{col 50}{space 3}0.908{col 58}{space 4}-.4587692{col 71}{space 3} .4077558
{txt}{space 8}0.treatc {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 16} {c |}
{space 1}presub3c#treatc {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2}-.0356471{col 30}{space 2} .2527255{col 41}{space 1}   -0.14{col 50}{space 3}0.888{col 58}{space 4}-.5311351{col 71}{space 3} .4598409
{txt}{space 16} {c |}
{space 6}1.presub2c {c |}{col 18}{res}{space 2} .4359908{col 30}{space 2} .2134769{col 41}{space 1}    2.04{col 50}{space 3}0.041{col 58}{space 4} .0174529{col 71}{space 3} .8545288
{txt}{space 16} {c |}
{space 1}presub2c#treatc {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2}-.3080791{col 30}{space 2} .2537194{col 41}{space 1}   -1.21{col 50}{space 3}0.225{col 58}{space 4}-.8055157{col 71}{space 3} .1893576
{txt}{space 16} {c |}
{space 6}1.presub1c {c |}{col 18}{res}{space 2}-.2275943{col 30}{space 2} .1706775{col 41}{space 1}   -1.33{col 50}{space 3}0.182{col 58}{space 4}-.5622208{col 71}{space 3} .1070322
{txt}{space 16} {c |}
{space 1}presub1c#treatc {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2} .1100735{col 30}{space 2} .2123645{col 41}{space 1}    0.52{col 50}{space 3}0.604{col 58}{space 4}-.3062836{col 71}{space 3} .5264306
{txt}{space 16} {c |}
{space 9}1.sub1c {c |}{col 18}{res}{space 2} .1780703{col 30}{space 2} .2244213{col 41}{space 1}    0.79{col 50}{space 3}0.428{col 58}{space 4}-.2619251{col 71}{space 3} .6180656
{txt}{space 16} {c |}
{space 4}sub1c#treatc {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2} .2666103{col 30}{space 2} .2765085{col 41}{space 1}    0.96{col 50}{space 3}0.335{col 58}{space 4} -.275506{col 71}{space 3} .8087266
{txt}{space 16} {c |}
{space 5}1.postsub1c {c |}{col 18}{res}{space 2} .0628776{col 30}{space 2} .2697772{col 41}{space 1}    0.23{col 50}{space 3}0.816{col 58}{space 4}-.4660414{col 71}{space 3} .5917967
{txt}{space 16} {c |}
postsub1c#treatc {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2}-.0514517{col 30}{space 2} .3019456{col 41}{space 1}   -0.17{col 50}{space 3}0.865{col 58}{space 4}-.6434395{col 71}{space 3} .5405361
{txt}{space 16} {c |}
{space 5}1.postsub2c {c |}{col 18}{res}{space 2}-.0494319{col 30}{space 2} .1957599{col 41}{space 1}   -0.25{col 50}{space 3}0.801{col 58}{space 4}-.4332344{col 71}{space 3} .3343707
{txt}{space 16} {c |}
postsub2c#treatc {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2}-.0224406{col 30}{space 2} .2248821{col 41}{space 1}   -0.10{col 50}{space 3}0.921{col 58}{space 4}-.4633393{col 71}{space 3} .4184582
{txt}{space 16} {c |}
{space 5}1.postsub3c {c |}{col 18}{res}{space 2}-.3093269{col 30}{space 2} .2403913{col 41}{space 1}   -1.29{col 50}{space 3}0.198{col 58}{space 4}-.7806327{col 71}{space 3} .1619789
{txt}{space 16} {c |}
postsub3c#treatc {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2} .3764996{col 30}{space 2} .2705373{col 41}{space 1}    1.39{col 50}{space 3}0.164{col 58}{space 4}-.1539097{col 71}{space 3} .9069089
{txt}{space 16} {c |}
{space 5}1.postsub4c {c |}{col 18}{res}{space 2}  -.29986{col 30}{space 2} .2337954{col 41}{space 1}   -1.28{col 50}{space 3}0.200{col 58}{space 4}-.7582339{col 71}{space 3}  .158514
{txt}{space 16} {c |}
postsub4c#treatc {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2}-.0380034{col 30}{space 2} .2753467{col 41}{space 1}   -0.14{col 50}{space 3}0.890{col 58}{space 4} -.577842{col 71}{space 3} .5018352
{txt}{space 16} {c |}
{space 5}1.postsub5c {c |}{col 18}{res}{space 2}  .124685{col 30}{space 2} .2106241{col 41}{space 1}    0.59{col 50}{space 3}0.554{col 58}{space 4}-.2882599{col 71}{space 3} .5376299
{txt}{space 16} {c |}
postsub5c#treatc {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2}-.2955354{col 30}{space 2} .2402878{col 41}{space 1}   -1.23{col 50}{space 3}0.219{col 58}{space 4}-.7666383{col 71}{space 3} .1755675
{txt}{space 16} {c |}
{space 5}1.postsub6c {c |}{col 18}{res}{space 2}-.0342217{col 30}{space 2} .2081028{col 41}{space 1}   -0.16{col 50}{space 3}0.869{col 58}{space 4}-.4422234{col 71}{space 3} .3737801
{txt}{space 16} {c |}
postsub6c#treatc {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2} .2130032{col 30}{space 2} .2417766{col 41}{space 1}    0.88{col 50}{space 3}0.378{col 58}{space 4}-.2610185{col 71}{space 3} .6870249
{txt}{space 16} {c |}
{space 5}1.postsub7c {c |}{col 18}{res}{space 2}-.1161529{col 30}{space 2} .2031754{col 41}{space 1}   -0.57{col 50}{space 3}0.568{col 58}{space 4}-.5144941{col 71}{space 3} .2821883
{txt}{space 16} {c |}
postsub7c#treatc {c |}
{space 12}1 0  {c |}{col 18}{res}{space 2} .0053318{col 30}{space 2} .2423768{col 41}{space 1}    0.02{col 50}{space 3}0.982{col 58}{space 4}-.4698667{col 71}{space 3} .4805302
{txt}{space 16} {c |}
{space 12}mage {c |}{col 18}{res}{space 2}-.0030772{col 30}{space 2} .0005498{col 41}{space 1}   -5.60{col 50}{space 3}0.000{col 58}{space 4}-.0041551{col 71}{space 3}-.0019994
{txt}{space 11}mage2 {c |}{col 18}{res}{space 2} .0000251{col 30}{space 2} 7.25e-06{col 41}{space 1}    3.47{col 50}{space 3}0.001{col 58}{space 4} .0000109{col 71}{space 3} .0000394
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0254413{col 30}{space 2}  .008588{col 41}{space 1}    2.96{col 50}{space 3}0.003{col 58}{space 4} .0086038{col 71}{space 3} .0422788
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}         id2{col 14}{c |}{space 1}    65631{col 27}{space 1}    65631{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}         cmt{col 14}{c |}{space 1}       96{col 27}{space 1}        0{col 39}{result}{space 1}       96{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store close6
{txt}
{com}. 
. 
. 
. esttab   close6 , se star(* 0.10 ** 0.05 *** 0.01) mtitles nogaps b(%8.3f) t(%6.2f)  scalars(N ) order(1.presub2c 1.presub1c 1.sub1c 1.postsub1c 1.postsub2c 1.postsub3c 1.postsub4c 1.postsub5c 1.postsub6c) keep(1.presub2c 1.presub1c 1.sub1c 1.postsub1c 1.postsub2c 1.postsub3c 1.postsub4c 1.postsub5c 1.postsub6c) 
{res}
{txt}{hline 28}
{txt}                      (1)   
{txt}                   close6   
{txt}{hline 28}
{txt}1.presub2c  {res}        0.436** {txt}
            {res} {ralign 12:{txt:(}0.213{txt:)}}   {txt}
{txt}1.presub1c  {res}       -0.228   {txt}
            {res} {ralign 12:{txt:(}0.171{txt:)}}   {txt}
{txt}1.sub1c     {res}        0.178   {txt}
            {res} {ralign 12:{txt:(}0.224{txt:)}}   {txt}
{txt}1.postsub1c {res}        0.063   {txt}
            {res} {ralign 12:{txt:(}0.270{txt:)}}   {txt}
{txt}1.postsub2c {res}       -0.049   {txt}
            {res} {ralign 12:{txt:(}0.196{txt:)}}   {txt}
{txt}1.postsub3c {res}       -0.309   {txt}
            {res} {ralign 12:{txt:(}0.240{txt:)}}   {txt}
{txt}1.postsub4c {res}       -0.300   {txt}
            {res} {ralign 12:{txt:(}0.234{txt:)}}   {txt}
{txt}1.postsub5c {res}        0.125   {txt}
            {res} {ralign 12:{txt:(}0.211{txt:)}}   {txt}
{txt}1.postsub6c {res}       -0.034   {txt}
            {res} {ralign 12:{txt:(}0.208{txt:)}}   {txt}
{txt}{hline 28}
{txt}N           {res}       153131   {txt}
{txt}{hline 28}
{txt}Standard errors in parentheses
{txt}* p<0.10, ** p<0.05, *** p<0.01

{com}. 
. esttab   close6  using "R:\WSV2\TBu_BMa\Subsidies Project\Results\c6.tex" ,replace  se nostar mtitles nogaps b(%8.3f) t(%6.2f)  scalars(N ) order(1.presub2c 1.presub1c 1.sub1c 1.postsub1c 1.postsub2c 1.postsub3c 1.postsub4c 1.postsub5c 1.postsub6c) keep(1.presub2c 1.presub1c 1.sub1c 1.postsub1c 1.postsub2c 1.postsub3c 1.postsub4c 1.postsub5c 1.postsub6c) 
{res}{txt}(note: file R:\WSV2\TBu_BMa\Subsidies Project\Results\c6.tex not found)
(output written to {browse  `"R:\WSV2\TBu_BMa\Subsidies Project\Results\c6.tex"'})

{com}. 
. 
. restore
{txt}
{com}. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}R:\WSV2\TBu_BMa\Subsidies Project\Results\Close Substitutes.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}22 Feb 2021, 11:13:09
{txt}{.-}
{smcl}
{txt}{sf}{ul off}